Businesses commonly use promotional schemes to improve sales volumes and profits. For instance, a business may adjust prices as needed to encourage sales of particular products. Likewise, businesses may specially present or advertise their products to increase consumer awareness and demand. To generate incremental revenue or expand market share, companies spend billions of dollars annually in promotional discounts, rebates, cash incentives, coupons, and subsidized financing. Because of the variety of promotions in play at any one time, the complexity of the market, and an inadequate understanding of customer response, few companies are able to accurately predict the overall effectiveness of their promotional spending.
The user making promotion decisions is faced with the challenge of how to best target promotional spending to achieve corporate goals at the lowest cost. To make this decision, the user needs to accurately forecast how a proposed promotion will affect revenues, profits, and sales volumes for each product. Likewise, the user needs to calculate how much each promotion will reduce on-hand inventory while minimizing cross-product and cross-segment dilution. The user further needs to predict how different market segments will react to different types of promotions. The user also needs to determine which combination of promotions will produce the highest return on expenditure while meeting sales, margin, and market share targets.
Therefore, there exists a further need for a system or method to accurately forecast the impact of promotions and to automate these tasks.